Parallel Point-to-Point Shortest Paths and Batch Queries
Xiaojun Dong, Andy Li, Yan Gu, Yihan Sun

TL;DR
Orionet introduces efficient parallel algorithms for point-to-point shortest path queries, including batch processing, using bidirectional search, heuristics, and shared information, outperforming existing solutions.
Contribution
The paper presents a novel parallel PPSP framework with bidirectional search and batch query extension, achieving significant speedups over baselines.
Findings
Bidirectional search in Orionet is 2.9× faster than GraphIt.
Bidirectional A* in Orionet is 4.4× faster than GraphIt.
Orionet significantly improves batch PPSP query performance.
Abstract
We propose Orionet, efficient parallel implementations of Point-to-Point Shortest Paths (PPSP) queries using bidirectional search (BiDS) and other heuristics, with an additional focus on batch PPSP queries. We present a framework for parallel PPSP built on existing single-source shortest paths (SSSP) frameworks by incorporating pruning conditions. As a result, we develop efficient parallel PPSP algorithms based on early termination, bidirectional search, A search, and bidirectional A all with simple and efficient implementations. We extend our idea to batch PPSP queries, which are widely used in real-world scenarios. We first design a simple and flexible abstraction to represent the batch so PPSP can leverage the shared information of the batch. Orionet formalizes the batch as a query graph represented by edges between queried sources and targets. In this way, we directly…
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